The present invention relates to a software algorithm for learning the minimum throttle position on an engine having an electronically controlled throttle actuator, and more particularly, to an algorithm capable of making multiple learning attempts in an effort to overcome a throttle obstruction.
For the purpose of this description and in the sections that follow, the term throttle is used to describe the mechanism that regulates the delivery of fuel, air, or air-fuel mixture to the engine in a motor vehicle. There may or may not be a mechanical linkage between the accelerator pedal and the throttle.
On throttle control systems without non-volatile memory and pop-up default air throttle positions, it is necessary for the subsystem to learn the minimum throttle position so that the throttle can be controlled with respect to that minimum position.
It has been found that during cold weather, ice can form in the bore of the throttle body resulting in a throttle obstruction that may prevent complete closing of the throttle and thus prevent learning of the actual throttle position minimum at power on. This can result in a xe2x80x9cService Engine Soonxe2x80x9d indication and less than optimal powertrain performance. In some cases, the system may go into a failsafe mode executing a limp home algorithm. Thus, accurate determination of the throttle position minimum is critical to the operation of the throttle control system and vehicle performance.
Such weather related obstruction problems can often be overcome by the use of higher capacity actuators or the addition of non-volatile memory, both of which increase system cost, or the use of more aggressive gear reduction, which negatively impacts system time response characteristics.
Various throttle control systems have been developed that include the use of sensors to detect and control throttle position including the learning of a fully closed throttle state.
The algorithm 200 shown in FIG. 2 is a known algorithm typical of the single strike ECU strategies that attempt to establish a minimum throttle position. The algorithm starts with step S202 to initialize a program timer. This is followed by step S204 wherein constants programmed at the time the algorithm is loaded onto the ECU to represent sensor minimum values are read for reference. In the next step, S206, a throttle sensor signal is received by the ECU. In the final step, S208, the throttle sensor reading is examined to determine whether it indicates a valid minimum throttle position. If the result is valid, normal engine startup proceeds; otherwise, a fault condition is raised and a failure indicator is communicated to the balance of the engine management system and, ultimately, to the operator. The prior art in this field is limited to such single strike learning techniques.
Consequently, there remains a need for a throttle control system that can accurately determine the minimum throttle position, including the ability to overcome minor throttle obstructions, prior to engine run state so that optimum engine performance can be achieved.
The present invention provides a system capable of making multiple attempts at learning a minimum throttle position in an effort to overcome a throttle obstruction. The determination of an accurate throttle minimum position is necessary to assure optimum vehicle performance.
In a preferred embodiment of the invention, a multi-strike throttle minimum learning system includes a pair of throttle position sensors, each producing a signal indicative of the position of an electronically actuated throttle valve. The throttle position signals are communicated to an ECU containing reusable memory and operable to execute an algorithm for controlling the minimum learning process during engine startup.
According to one preferred method of learning the throttle position minimum, a software algorithm first initializes a learn-attempt counter and stores a predetermined throttle minimum position value range based on throttle system component tolerances. Signals from the throttle position sensors are received and compared to the pre-established throttle minimum value range. If the sensors indicate that a valid throttle minimum position is established, the ECU saves the minimum position value and execution of the algorithm is terminated. If a valid minimum throttle position is not sensed, a throttle obstruction is assumed and subsequent learn attempts are made until either a valid throttle position minimum is sensed, indicating that the obstruction was overcome, or a predetermined maximum number of learn attempts is reached, with the appropriate result being communicated by the ECU to certain preselected subsystems of the vehicle. Between learn attempts, power to the system is deactivated for a predetermined delay period and then reapplied so that the throttle actuator can attempt to place the throttle valve in a full closed position. In another feature of the preferred embodiment, the execution of the algorithm is terminated if a sensor fault is detected.
Accordingly, it is one object of the invention to provide improved algorithm for learning the minimum throttle position on an engine having an electronically controlled throttle actuator. These and other objects, advantages and features are accomplished according to the devices and assemblies of the present invention.